Update README.md

README.md

@@ -178,7 +178,90 @@ curl http://localhost:30000/v1/chat/completions \
 
 ## Function call
 
-### 1. `vLLM`
+### 1.  `transformers`
+
+<details><summary>Click for a dropdown</summary>
+
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
+import json
+import re
+REGEX_FUNCTION_CALL_V3 = re.compile(r"function call<\|role_sep\|>\n(.*)$", re.DOTALL)
+REGEX_CONTENT_PATTERN = re.compile(r"^(.*?)<\|message_sep\|>", re.DOTALL)
+def parse_function_and_content(completion_str: str):
+    """
+    Using the regexes the user provided, attempt to extract function call and content.
+    Returns (function_call_str_or_None, content_str_or_None)
+    """
+
+    function_call = None
+    content = None
+
+    m_func = REGEX_FUNCTION_CALL_V3.search(completion_str)
+    if m_func:
+        try:
+            function_call = json.loads(m_func.group(1))
+            if isinstance(function_call, dict) and "name" in function_call and "arguments" in function_call:
+                if not isinstance(function_call["arguments"], dict):
+                    function_call = None
+            else:
+                function_call = None
+        except json.JSONDecodeError:
+            function_call = None
+
+            # will return raw string in failed attempt of function calling
+            return function_call, completion_str
+
+    m_content = REGEX_CONTENT_PATTERN.search(completion_str)
+    if m_content:
+        content = m_content.group(1)
+    else:
+        # as a fallback, everything before the first message_sep marker if present
+        if "<|message_sep|>" in completion_str:
+            content = completion_str.split("<|message_sep|>")[0]
+        else:
+            content = completion_str
+
+    return function_call, content
+
+model_name = "ai-sage/GigaChat3-10B-A1.8B"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
+model.generation_config = GenerationConfig.from_pretrained(model_name)
+tools = [
+    {
+      "type": "function",
+      "function": {
+        "name": "get_weather",
+        "description": "Получить информацию о текущей погоде в указанном городе.",
+        "parameters": {
+          "type": "object",
+          "properties": {
+            "city": {
+              "type": "string",
+              "description": "Название города (например, Москва, Казань)."
+            }
+          },
+          "required": ["city"]
+        }
+      }
+    }
+]
+messages = [
+    {"role": "user", "content": "Какая сейчас погода в Москве?"}
+]
+input_tensor = tokenizer.apply_chat_template(messages, tools=tools, add_generation_prompt=True, return_tensors="pt")
+outputs = model.generate(input_tensor.to(model.device), max_new_tokens=1000)
+
+result = parse_function_and_content(tokenizer.decode(outputs[0][input_tensor.shape[1]:], skip_special_tokens=False))[0]
+print(result)
+```
+
+</details>
+
+
+### 2. `vLLM`
 
 Соберите dev версию, коммит>=[21bb323](https://github.com/vllm-project/vllm/tree/21bb323542bad9d7a7206d949f33734caf48c40c))
 
@@ -228,7 +311,7 @@ curl http://localhost:8000/v1/chat/completions \
 }'
 ```
 
-### 2. `SGLang`
+### 3. `SGLang`
 
 Соберите dev версию на данной ветке - https://github.com/sgl-project/sglang/pull/14765.